Beyond sentential semantic parsing: Tackling the math sat with a cascade of tree transducers

Mark Hopkins, Cristian Petrescu-Prahova, Roie Levin, Ronan Le Bras, Alvaro Herrasti, Vidur Joshi*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present an approach for answering questions that span multiple sentences and exhibit sophisticated cross-sentence anaphoric phenomena, evaluating on a rich source of such questions – the math portion of the Scholastic Aptitude Test (SAT). By using a tree transducer cascade as its basic architecture, our system (called EUCLID) propagates uncertainty from multiple sources (e.g. coreference resolution or verb interpretation) until it can be confidently resolved. Experiments show the first-ever results (43% recall and 91% precision) on SAT algebra word problems. We also apply EUCLID to the public Dolphin algebra question set, and improve the state-of-the-art F1-score from 73.9% to 77.0%.

Original languageEnglish
Title of host publicationEMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages795-804
Number of pages10
ISBN (Electronic)9781945626838
DOIs
StatePublished - 2017
Externally publishedYes
Event2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017 - Copenhagen, Denmark
Duration: 9 Sep 201711 Sep 2017

Publication series

NameEMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings

Conference

Conference2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017
Country/TerritoryDenmark
CityCopenhagen
Period9/09/1711/09/17

Fingerprint

Dive into the research topics of 'Beyond sentential semantic parsing: Tackling the math sat with a cascade of tree transducers'. Together they form a unique fingerprint.

Cite this